Inplantable devices for sensing physiological parameters (e.g., pressure or flow rate in a blood lumen) are known, e.g., an implanted sensor system configured to sample a physiological signal at an implantation site in a body. In order to retrieve clinic information from the sampled physiological signal, the original signal has to be sampled with sufficient accuracy and rate. The key operating parameters for sampling include: the sampling time, i.e., when is the signal sampled, the time span between the first and last measurement, whether the signal is quasi-periodic, when (within the sample period) the signal measured, the sampling rate, the measurement range (e.g. the minimum and maximum signal values that the sensor may sense), and the signal resolution (e.g. the minimal change in signal magnitude that would alter the resulting reading).
If the sensor includes a trigger mechanism, e.g. start to sample when the signal level goes below a threshold, then the parameters of the trigger mechanism also affect the quality of the measurements and the resources needed to generate them. When operated with the most stringent values for these parameters, the sensor may provide clinically relevant information, but the resources required to obtain such information may be too high, especially power consumption, but also in terms of the size, complexity, and throughput.
If the sensor is embedded in an implant, and especially if this implant operates using an acoustic switch, then sampling may take a significant proportion of the power budget of the implant. Since the sensor consumes practically no power when idle, most of its power budget is allocated to taking measurements. The more measurements it takes per exam, the fewer exams it can perform. An exam is a term used to measure a physiologically relevant value at a given point of time, for instance, systemic blood pressure. The resolution relates to the number of sampled bits. Sampling at higher resolution (for example, 1000 distinct signal levels) would require more power than sampling at lower resolution. When the signal range is diminished, one can reduce the number of distinct signal levels and keep the resolution, and thus save power.
Saving power is only one part of the problem. When optimizing the sampling parameters, one can sample fewer measurements, and thus require a smaller buffer to hold them. If the samples are transmitted to a medical system, either extracorporeal or implanted, the transmission bandwidth may be limited. Sampling fewer measurements may enable transmission that would otherwise not be possible. Reducing the signal range that the sensor needs to sample may reduce the size, cost, and complexity of the sensor.